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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be considered an asset Proven record in publication
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, excursions) Global geo-/paleomagnetic field modelling expertise is advantageous Strong programming skills, preferably in Fortran, Python and/or Matlab, parallel programming Experience in international
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opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key
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part of a team, be happy to share thoughts and receive feedback from other team members, and be able to carry out parallel tasks In addition, it is preferable that you: Have experience with processing
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platform enables us to test hundreds of different conditions in parallel and assess their impacts on human immune responses, such as antibody production. We routinely work with industry partners to exploit
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to an entrepreneurial ecosystem directly related to its industrial and socio-economic environment in Morocco and Africa. HTMR provides highly automated and parallel approaches to the development of new materials and
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have experience with interactive visualisation of uncertainty (e.g., dashboards, uncertainty mapping). You have experience with HPC or parallel computing for computationally intensive tasks. Our offer A